diff --git a/dev-0/out.tsv b/dev-0/out.tsv
new file mode 100644
index 0000000..17903bb
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diff --git a/geval b/geval
new file mode 100755
index 0000000..b68b316
Binary files /dev/null and b/geval differ
diff --git a/kMeans.ipynb b/kMeans.ipynb
new file mode 100644
index 0000000..e23fc37
--- /dev/null
+++ b/kMeans.ipynb
@@ -0,0 +1,70 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "f7e1ae0d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import csv\n",
+    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
+    "from sklearn.cluster import KMeans"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "7582a8dd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#dev0\n",
+    "dev0_data = pd.read_csv('dev-0/in.tsv', header=None, quoting=csv.QUOTE_NONE, sep='\\t')\n",
+    "\n",
+    "dev0_y = KMeans(n_clusters=50).fit_predict(TfidfVectorizer().fit_transform(dev0_data[0].values))\n",
+    "\n",
+    "#zapis wyników\n",
+    "dev0_y.tofile('dev-0/out.tsv', sep='\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "d3c75abc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#TestA\n",
+    "testA_data = pd.read_csv('test-A/in.tsv', header=None, quoting=csv.QUOTE_NONE, sep='\\t')\n",
+    "\n",
+    "testA_y = KMeans(n_clusters=50).fit_predict(TfidfVectorizer().fit_transform(testA_data[0].values))\n",
+    "\n",
+    "#zapis wyników\n",
+    "testA_y.tofile('test-A/out.tsv', sep='\\n')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/kMeans.py b/kMeans.py
new file mode 100644
index 0000000..ad11f84
--- /dev/null
+++ b/kMeans.py
@@ -0,0 +1,35 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# In[1]:
+
+
+import pandas as pd
+import csv
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.cluster import KMeans
+
+
+# In[2]:
+
+
+#dev0
+dev0_data = pd.read_csv('dev-0/in.tsv', header=None, quoting=csv.QUOTE_NONE, sep='\t')
+
+dev0_y = KMeans(n_clusters=50).fit_predict(TfidfVectorizer().fit_transform(dev0_data[0].values))
+
+#zapis wyników
+dev0_y.tofile('dev-0/out.tsv', sep='\n')
+
+
+# In[3]:
+
+
+#TestA
+testA_data = pd.read_csv('test-A/in.tsv', header=None, quoting=csv.QUOTE_NONE, sep='\t')
+
+testA_y = KMeans(n_clusters=50).fit_predict(TfidfVectorizer().fit_transform(testA_data[0].values))
+
+#zapis wyników
+testA_y.tofile('test-A/out.tsv', sep='\n')
+
diff --git a/test-A/out.tsv b/test-A/out.tsv
new file mode 100644
index 0000000..bc77e7b
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